1. Field of the Invention
The present invention relates to sensors for identifying blade damage in turbine engines. Embodiments of the invention provide systems and methods for detecting and/or identifying damage to turbomachinery blades, such as foreign object damage (FOD). Such systems are capable of detecting blade damage while the rotor is running and can drive a condition based maintenance approach to engines providing a cost savings as compared with traditional schedule based approaches.
2. Description of Related Art
US military fixed and rotary wing aircraft are increasingly being required to reliably operate in harsh environments and within more demanding operational envelopes. Foreign Object Damage (FOD) to gas turbine engines can result when debris is ingested by the engine which can compromise engine operation and safety. Harmful debris is typically categorized as originating either from a domestic object (part of the engine dislodging, such as a screw) or a foreign object (an object not part of the engine, for example, a bird).
Foreign object damage (FOD) is the primary driver for unscheduled engine removals in the current military fleet environment. To maintain affordability and fleet readiness, there is a need for identifying the FOD event and location and the magnitude of the FOD damage must be assessed while the engine is still on wing. It is important to note that the principal reason for performing FOD inspections is to detect small levels of damage before subsequent usage can cause that damage to expand into a serious risk of engine failure. The worst case scenario for the current method of inspection is for a minor FOD event to have gone undetected, due to a lack of inspection based on schedule or failure to detect the damage, and then result in a later failure of the engine causing loss of life or total loss of the asset.
There is currently a lack of reliable instrumentation which can provide data about noncatastrophic FOD without an extended examination by a highly skilled technician. Current methods require a detailed visual inspection either through engine disassembly or with a borescope. Such a process becomes increasingly difficult as engines and airframes become more and more integrated, as the access to necessary points on the engine becomes limited. Further, without knowing that a FOD event has occurred, there is no way to determine the optimal points in time at which an engine should be inspected. This leads to the inefficient schedule-based maintenance approach where all engines, regardless of potential damage, are inspected on a regular basis in the hopes of identifying blade damage early so that it can be corrected before engine failure. As a result, this constitutes a time consuming and very expensive approach toward obtaining the needed information. Real-time condition monitoring of FOD in gas turbine engines is thus highly desired.
There are a variety of methods currently used for FOD detection. Some methods analyze stress or ultrasound wave signals, others analyze reflected light and microwave signals, and still others measure and analyze eddy currents and discharge pressure. Such methods may use timing as a central concept of the algorithm, while others use static data, i.e., data that does not have a time component. Methods that are time-based typically use specific timing features as a parameter to determine another metric such as vibration or stagger angle, which may be representative of FOD. A disadvantage of existing FOD detection systems is they often have complex hardware components leading to increased weight and implementation costs.
One existing approach is disclosed in U.S. Published Patent Application, Publication No. 2011/0041474, entitled “Method and System for Detecting the Ingestion of an Object by an Aircraft Turbine Engine During a Mission.” This approach uses a digital camera to take pictures of the turbine blades at a rate comparable to the rate of revolution. The digital photographs are then processed and compared to photographs of the blades from previous revolutions. Should the processing algorithm realize a difference in the photographs, the system alerts the end user that FOD has been detected.
Other existing methods of identifying FOD are disclosed in U.S. Published Patent Application, Publication No. 2012/0035861, entitled “Blade Monitoring System.” This approach uses one or more laser probes, magnetic sensors, capacitive sensors, microwave sensors, or an eddy current sensor to sense the passing of blades. The signals obtained by the sensors are then passed through a network of analog signal splitters and analog-to-digital converters, after which the signals from the converter outputs are analyzed. The signal waveforms, measured on a time scale, are analyzed using techniques including the calculation of interpolated threshold crossings, average threshold crossings, a centroid of the pulse, time of arrival, and the change of time of arrival. The system also senses and receives a timing reference which is used to calculate the time of arrival, and receives a stored expected time of arrival which is used to calculate the change of time of arrival. The change of time of arrival is then used to determine natural frequency, vibration, and static lean angle as a means to determine blade damage.
Another approach is disclosed in U.S. Pat. No. 7,941,281, entitled “System and Method for Rotor Blade Health Monitoring.” This approach uses time of arrival sensors to obtain signals indicative of the times of arrival of rotating rotor blades. The signals are then used to determine one or more features of the blades including static and dynamic deflection, clearance, blades twist profile, frequency detuning during operation. These features are then used by a physics and reliability modeler to estimate rotor blade crack length, rotor blade crack propagation time, and probability of rotor blade crack. The data is then used by a decision level fuser to determine the health of the rotating rotor blades.
The approaches of such systems and methods lack one or more of reliability, accuracy, and sensitivity in detecting the presence of damaged blades. What is needed is an accurate and reliable approach capable of detecting even very minor levels of blade damage. Such techniques would include the incorporation of one or more of: a unique blade fingerprint analysis method, use of more reliable timing differencing techniques, reliance on unique timing features, and the performance of one or more complex statistical analyses on the data, such as Short Time Fourier Transform to produce spectrograms.